```html
<!DOCTYPE html>
<html lang="zh-CN">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>DJL预训练模型教程 - 深度学习实践指南</title>
    <link rel="stylesheet" href="https://cdn.staticfile.org/font-awesome/6.4.0/css/all.min.css">
    <link rel="stylesheet" href="https://cdn.staticfile.org/tailwindcss/2.2.19/tailwind.min.css">
    <link href="https://fonts.googleapis.com/css2?family=Noto+Serif+SC:wght@400;500;600;700&family=Noto+Sans+SC:wght@300;400;500;700&display=swap" rel="stylesheet">
    <script src="https://cdn.jsdelivr.net/npm/mermaid@latest/dist/mermaid.min.js"></script>
    <style>
        body {
            font-family: 'Noto Sans SC', 'Noto Serif SC', Tahoma, Arial, Roboto, "Droid Sans", "Helvetica Neue", "Droid Sans Fallback", "Heiti SC", "Hiragino Sans GB", Simsun, sans-serif;
            color: #333;
            background-color: #f9fafb;
            line-height: 1.6;
        }
        .hero-gradient {
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
        }
        .code-block {
            background-color: #2d3748;
            border-radius: 0.5rem;
            color: #e2e8f0;
            position: relative;
        }
        .code-header {
            background-color: #1a202c;
            border-top-left-radius: 0.5rem;
            border-top-right-radius: 0.5rem;
            padding: 0.5rem 1rem;
            color: #a0aec0;
            font-family: monospace;
            font-size: 0.875rem;
        }
        .card-hover {
            transition: all 0.3s ease;
        }
        .card-hover:hover {
            transform: translateY(-5px);
            box-shadow: 0 20px 25px -5px rgba(0, 0, 0, 0.1), 0 10px 10px -5px rgba(0, 0, 0, 0.04);
        }
        .highlight {
            position: relative;
        }
        .highlight::after {
            content: '';
            position: absolute;
            bottom: 0;
            left: 0;
            width: 100%;
            height: 30%;
            background-color: rgba(102, 126, 234, 0.2);
            z-index: -1;
            transition: all 0.3s ease;
        }
        .highlight:hover::after {
            height: 50%;
        }
        .section-divider {
            position: relative;
            height: 80px;
            overflow: hidden;
        }
        .section-divider svg {
            position: absolute;
            top: 0;
            left: 0;
            width: 100%;
            height: 100%;
        }
    </style>
</head>
<body>
    <!-- Hero Section -->
    <section class="hero-gradient text-white py-20 px-4 sm:px-6 lg:px-8">
        <div class="max-w-4xl mx-auto text-center">
            <h1 class="text-4xl md:text-5xl font-bold mb-4 leading-tight">深度学习预训练模型实战</h1>
            <h2 class="text-xl md:text-2xl font-medium mb-6 opacity-90">使用DJL快速构建AI应用</h2>
            <p class="text-lg md:text-xl mb-8 max-w-2xl mx-auto opacity-90">掌握预训练模型的核心概念与应用技巧，加速您的AI开发流程</p>
            <div class="flex justify-center space-x-4">
                <a href="#intro" class="bg-white text-indigo-700 hover:bg-gray-100 px-6 py-3 rounded-full font-medium transition duration-300 shadow-md">开始学习</a>
                <a href="#demo" class="border-2 border-white text-white hover:bg-white hover:text-indigo-700 px-6 py-3 rounded-full font-medium transition duration-300">查看示例</a>
            </div>
        </div>
    </section>

    <!-- Main Content -->
    <div class="max-w-6xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
        <!-- Introduction Section -->
        <section id="intro" class="mb-20">
            <div class="flex items-center mb-8">
                <div class="h-1 bg-indigo-500 w-12 rounded-full"></div>
                <h2 class="ml-4 text-2xl font-bold text-gray-800">预训练模型简介</h2>
            </div>
            <div class="grid md:grid-cols-2 gap-8">
                <div>
                    <p class="text-lg text-gray-700 mb-6">预训练模型是深度学习中的一种重要工具，能够加速模型开发过程，并且能够在已有知识的基础上进行更好的任务适配。在本教程中，我们将通过 DJL（Deep Java Library）来展示如何加载和使用预训练模型。</p>
                    
                    <div class="bg-white p-6 rounded-xl shadow-md mb-6">
                        <h3 class="text-xl font-semibold mb-4 text-indigo-700 flex items-center">
                            <i class="fas fa-lightbulb mr-2"></i> 核心优势
                        </h3>
                        <ul class="space-y-3">
                            <li class="flex items-start">
                                <i class="fas fa-check-circle text-green-500 mt-1 mr-2"></i>
                                <span>避免从零开始训练，节省计算资源</span>
                            </li>
                            <li class="flex items-start">
                                <i class="fas fa-check-circle text-green-500 mt-1 mr-2"></i>
                                <span>在大规模数据集上预训练，具备更强的泛化能力</span>
                            </li>
                            <li class="flex items-start">
                                <i class="fas fa-check-circle text-green-500 mt-1 mr-2"></i>
                                <span>通过微调即可适配多种下游任务</span>
                            </li>
                        </ul>
                    </div>
                </div>
                
                <!-- Mermaid Diagram -->
                <div class="bg-white p-6 rounded-xl shadow-md">
                    <div class="mermaid">
                        graph TD
                            A[大规模数据集] --> B[预训练模型]
                            B --> C[图像分类]
                            B --> D[文本生成]
                            B --> E[目标检测]
                            B --> F[语音识别]
                            style A fill:#6366F1,color:#fff
                            style B fill:#7C3AED,color:#fff
                            style C fill:#10B981,color:#fff
                            style D fill:#3B82F6,color:#fff
                            style E fill:#F59E0B,color:#fff
                            style F fill:#EC4899,color:#fff
                    </div>
                </div>
            </div>
        </section>

        <!-- Section Divider -->
        <div class="section-divider my-16">
            <svg viewBox="0 0 1200 120" preserveAspectRatio="none">
                <path d="M0,0V46.29c47.79,22.2,103.59,32.17,158,28,70.36-5.37,136.33-33.31,206.8-37.5C438.64,32.43,512.34,53.67,583,72.05c69.27,18,138.3,24.88,209.4,13.08,36.15-6,69.85-17.84,104.45-29.34C989.49,25,1113-14.29,1200,52.47V0Z" opacity=".25" fill="#667eea"></path>
                <path d="M0,0V15.81C13,36.92,27.64,56.86,47.69,72.05,99.41,111.27,165,111,224.58,91.58c31.15-10.15,60.09-26.07,89.67-39.8,40.92-19,84.73-46,130.83-49.67,36.26-2.85,70.9,9.42,98.6,31.56,31.77,25.39,62.32,62,103.63,73,40.44,10.79,81.35-6.69,119.13-24.28s75.16-39,116.92-43.05c59.73-5.85,113.28,22.88,168.9,38.84,30.2,8.66,59,6.17,87.09-7.5,22.43-10.89,48-26.93,60.65-49.24V0Z" opacity=".5" fill="#667eea"></path>
                <path d="M0,0V5.63C149.93,59,314.09,71.32,475.83,42.57c43-7.64,84.23-20.12,127.61-26.46,59-8.63,112.48,12.24,165.56,35.4C827.93,77.22,886,95.24,951.2,90c86.53-7,172.46-45.71,248.8-84.81V0Z" fill="#667eea"></path>
            </svg>
        </div>

        <!-- Model Selection Section -->
        <section class="mb-20">
            <div class="flex items-center mb-8">
                <div class="h-1 bg-indigo-500 w-12 rounded-full"></div>
                <h2 class="ml-4 text-2xl font-bold text-gray-800">选择预训练模型</h2>
            </div>
            
            <div class="grid md:grid-cols-3 gap-6">
                <!-- Model Card 1 -->
                <div class="bg-white rounded-xl shadow-md overflow-hidden card-hover">
                    <div class="bg-indigo-100 p-4">
                        <i class="fas fa-image text-indigo-600 text-3xl"></i>
                    </div>
                    <div class="p-6">
                        <h3 class="text-xl font-bold text-gray-800 mb-2">ResNet</h3>
                        <p class="text-gray-600 mb-4">用于图像分类任务的经典CNN架构，具有残差连接设计，有效解决深度网络训练难题。</p>
                        <div class="flex flex-wrap gap-2">
                            <span class="bg-indigo-100 text-indigo-800 text-xs px-3 py-1 rounded-full">图像分类</span>
                            <span class="bg-indigo-100 text-indigo-800 text-xs px-3 py-1 rounded-full">CNN</span>
                            <span class="bg-indigo-100 text-indigo-800 text-xs px-3 py-1 rounded-full">计算机视觉</span>
                        </div>
                    </div>
                </div>
                
                <!-- Model Card 2 -->
                <div class="bg-white rounded-xl shadow-md overflow-hidden card-hover">
                    <div class="bg-blue-100 p-4">
                        <i class="fas fa-language text-blue-600 text-3xl"></i>
                    </div>
                    <div class="p-6">
                        <h3 class="text-xl font-bold text-gray-800 mb-2">BERT</h3>
                        <p class="text-gray-600 mb-4">基于Transformer的双向预训练语言模型，在多种NLP任务中表现优异，如文本分类、问答等。</p>
                        <div class="flex flex-wrap gap-2">
                            <span class="bg-blue-100 text-blue-800 text-xs px-3 py-1 rounded-full">NLP</span>
                            <span class="bg-blue-100 text-blue-800 text-xs px-3 py-1 rounded-full">Transformer</span>
                            <span class="bg-blue-100 text-blue-800 text-xs px-3 py-1 rounded-full">文本理解</span>
                        </div>
                    </div>
                </div>
                
                <!-- Model Card 3 -->
                <div class="bg-white rounded-xl shadow-md overflow-hidden card-hover">
                    <div class="bg-purple-100 p-4">
                        <i class="fas fa-robot text-purple-600 text-3xl"></i>
                    </div>
                    <div class="p-6">
                        <h3 class="text-xl font-bold text-gray-800 mb-2">GPT</h3>
                        <p class="text-gray-600 mb-4">基于Transformer的自回归语言模型，擅长文本生成任务，可根据上下文生成连贯文本。</p>
                        <div class="flex flex-wrap gap-2">
                            <span class="bg-purple-100 text-purple-800 text-xs px-3 py-1 rounded-full">文本生成</span>
                            <span class="bg-purple-100 text-purple-800 text-xs px-3 py-1 rounded-full">Transformer</span>
                            <span class="bg-purple-100 text-purple-800 text-xs px-3 py-1 rounded-full">语言模型</span>
                        </div>
                    </div>
                </div>
            </div>
        </section>

        <!-- Environment Setup Section -->
        <section class="mb-20">
            <div class="flex items-center mb-8">
                <div class="h-1 bg-indigo-500 w-12 rounded-full"></div>
                <h2 class="ml-4 text-2xl font-bold text-gray-800">配置开发环境</h2>
            </div>
            
            <div class="bg-white rounded-xl shadow-md overflow-hidden">
                <div class="code-header">
                    <i class="fas fa-code mr-2"></i>pom.xml
                </div>
                <div class="code-block p-4 overflow-x-auto">
                    <pre class="text-sm"><code class="language-xml">&lt;parent&gt;
    &lt;groupId&gt;org.springframework.boot&lt;/groupId&gt;
    &lt;artifactId&gt;spring-boot-starter-parent&lt;/artifactId&gt;
    &lt;version&gt;3.4.0&lt;/version&gt;
    &lt;relativePath/&gt;
&lt;/parent&gt;

&lt;groupId&gt;com.ts&lt;/groupId&gt;
&lt;artifactId&gt;java-djl&lt;/artifactId&gt;
&lt;version&gt;0.0.1-SNAPSHOT&lt;/version&gt;

&lt;properties&gt;
    &lt;djl.version&gt;0.11.0&lt;/djl.version&gt;
&lt;/properties&gt;

&lt;repositories&gt;
    &lt;repository&gt;
        &lt;id&gt;djl.ai&lt;/id&gt;
        &lt;url&gt;https://oss.sonatype.org/content/repositories/snapshots/&lt;/url&gt;
    &lt;/repository&gt;
&lt;/repositories&gt;

&lt;dependencyManagement&gt;
    &lt;dependencies&gt;
        &lt;dependency&gt;
            &lt;groupId&gt;ai.djl&lt;/groupId&gt;
            &lt;artifactId&gt;bom&lt;/artifactId&gt;
            &lt;version&gt;${djl.version}&lt;/version&gt;
            &lt;type&gt;pom&lt;/type&gt;
            &lt;scope&gt;import&lt;/scope&gt;
        &lt;/dependency&gt;
    &lt;/dependencies&gt;
&lt;/dependencyManagement&gt;
&lt;dependencies&gt;
    &lt;dependency&gt;
        &lt;groupId&gt;org.springframework.boot&lt;/groupId&gt;
        &lt;artifactId&gt;spring-boot-starter-web&lt;/artifactId&gt;
    &lt;/dependency&gt;

    &lt;dependency&gt;
        &lt;groupId&gt;org.springframework.boot&lt;/groupId&gt;
        &lt;artifactId&gt;spring-boot-starter-test&lt;/artifactId&gt;
        &lt;scope&gt;test&lt;/scope&gt;
    &lt;/dependency&gt;

    &lt;dependency&gt;
        &lt;groupId&gt;ai.djl&lt;/groupId&gt;
        &lt;artifactId&gt;model-zoo&lt;/artifactId&gt;
        &lt;version&gt;${djl.version}&lt;/version&gt;
    &lt;/dependency&gt;
    &lt;dependency&gt;
        &lt;groupId&gt;ai.djl.mxnet&lt;/groupId&gt;
        &lt;artifactId&gt;mxnet-model-zoo&lt;/artifactId&gt;
        &lt;version&gt;${djl.version}&lt;/version&gt;
    &lt;/dependency&gt;
    &lt;dependency&gt;
        &lt;groupId&gt;ai.djl.mxnet&lt;/groupId&gt;
        &lt;artifactId&gt;mxnet-engine&lt;/artifactId&gt;
        &lt;version&gt;${djl.version}&lt;/version&gt;
    &lt;/dependency&gt;
    &lt;dependency&gt;
        &lt;groupId&gt;ai.djl.mxnet&lt;/groupId&gt;
        &lt;artifactId&gt;mxnet-native-auto&lt;/artifactId&gt;
        &lt;version&gt;1.6.0&lt;/version&gt;
        &lt;scope&gt;runtime&lt;/scope&gt;
    &lt;/dependency&gt;
    &lt;dependency&gt;
        &lt;groupId&gt;org.projectlombok&lt;/groupId&gt;
        &lt;artifactId&gt;lombok&lt;/artifactId&gt;
        &lt;version&gt;RELEASE&lt;/version&gt;
        &lt;scope&gt;compile&lt;/scope&gt;
    &lt;/dependency&gt;
&lt;/dependencies&gt;
&lt;build&gt;
    &lt;finalName&gt;${project.artifactId}&lt;/finalName&gt;
    &lt;plugins&gt;
        &lt;plugin&gt;
            &lt;groupId&gt;org.springframework.boot&lt;/groupId&gt;
            &lt;artifactId&gt;spring-boot-maven-plugin&lt;/artifactId&gt;
            &lt;executions&gt;
                &lt;execution&gt;
                    &lt;goals&gt;
                        &lt;goal&gt;repackage&lt;/goal&gt;
                    &lt;/goals&gt;
                &lt;/execution&gt;
            &lt;/executions&gt;
        &lt;/plugin&gt;
    &lt;/plugins&gt;
&lt;/build&gt;</code></pre>
                </div>
            </div>
            
            <div class="mt-8 bg-white rounded-xl shadow-md overflow-hidden">
                <div class="code-header">
                    <i class="fas fa-cog mr-2"></i>application.yml
                </div>
                <div class="code-block p-4 overflow-x-auto">
                    <pre class="text-sm"><code class="language-yaml">djl:
  # 设定应用种类
  application-type: OBJECT_DETECTION
  # 设定输入数据格式
  input-class: java.awt.image.BufferedImage
  # 设定输出数据格式
  output-class: ai.djl.modality.cv.output.DetectedObjects
  # 设定一个筛选器来筛选你的模型
  model-filter:
    size: 512
  # 覆写已有的输入输出配置
  arguments:
    threshold: 0.5 # 只展示预测结果大于等于 0.5</code></pre>
                </div>
            </div>
        </section>

        <!-- Demo Section -->
        <section id="demo" class="mb-20">
            <div class="flex items-center mb-8">
                <div class="h-1 bg-indigo-500 w-12 rounded-full"></div>
                <h2 class="ml-4 text-2xl font-bold text-gray-800">图像识别示例</h2>
            </div>
            
            <div class="grid md:grid-cols-2 gap-8">
                <div>
                    <h3 class="text-xl font-semibold mb-4 text-gray-800">代码实现</h3>
                    <div class="bg-white rounded-xl shadow-md overflow-hidden">
                        <div class="code-header">
                            <i class="fas fa-code mr-2"></i>ImageDetectController.java
                        </div>
                        <div class="code-block p-4 overflow-x-auto">
                            <pre class="text-sm"><code class="language-java">@Slf4j
@RestController
public class ImageDetectController {

    @PostMapping(value = "/upload", produces = MediaType.IMAGE_PNG_VALUE)
    public ResponseEntity&lt;String&gt; diagnose(@RequestParam("file") MultipartFile file) throws ModelException, TranslateException, IOException {
        byte[] bytes = file.getBytes();
        Path imageFile = Paths.get(Objects.requireNonNull(file.getOriginalFilename()));
        Files.write(imageFile, bytes);
        return predict(imageFile);
    }

    public ResponseEntity&lt;String&gt; predict(Path imageFile) throws IOException, ModelException, TranslateException {
        Image img = ImageFactory.getInstance().fromFile(imageFile);

        Criteria&lt;Image, DetectedObjects&gt; criteria =
                Criteria.builder()
                        .optApplication(Application.CV.OBJECT_DETECTION)
                        .setTypes(Image.class, DetectedObjects.class)
                        .optFilter("backbone", "resnet50")
                        .optProgress(new ProgressBar())
                        .build();

        try (ZooModel&lt;Image, DetectedObjects&gt; model = ModelZoo.loadModel(criteria)) {
            try (Predictor&lt;Image, DetectedObjects&gt; predictor = model.newPredictor()) {
                DetectedObjects detection = predictor.predict(img);
                return saveBoundingBoxImage(img, detection);
            }
        }
    }

    private ResponseEntity&lt;String&gt; saveBoundingBoxImage(Image img, DetectedObjects detection) throws IOException {
        Path outputDir = Paths.get("src/main/resources");
        Files.createDirectories(outputDir);

        Image newImage = img.duplicate(Image.Type.TYPE_INT_ARGB);
        newImage.drawBoundingBoxes(detection);

        Path imagePath = outputDir.resolve("detected.png");
        newImage.save(Files.newOutputStream(imagePath), "png");
        log.info("Detected objects image has been saved in:{}" , imagePath);

        String fileDownloadUri = ServletUriComponentsBuilder.fromCurrentContextPath()
                .path("get")
                .toUriString();

        return ResponseEntity.ok(fileDownloadUri);
    }

    @GetMapping(value = "/get", produces = MediaType.IMAGE_PNG_VALUE)
    public @ResponseBody byte[] getImageWithMediaType() throws IOException {
        InputStream in = new ClassPathResource("detected.png").getInputStream();
        return IOUtils.toByteArray(in);
    }
}</code></pre>
                        </div>
                    </div>
                </div>
                
                <div>
                    <h3 class="text-xl font-semibold mb-4 text-gray-800">效果展示</h3>
                    <div class="bg-white p-6 rounded-xl shadow-md">
                        <div class="mb-6">
                            <h4 class="font-medium text-gray-700 mb-2">1. 启动项目</h4>
                            <img src="https://cdn.nlark.com/yuque/0/2024/png/21449790/1734155058419-b04f6b70-449d-4518-9cbb-f06b3ef3fe9e.png" alt="启动项目" class="rounded-lg shadow-sm w-full">
                        </div>
                        <div class="mb-6">
                            <h4 class="font-medium text-gray-700 mb-2">2. 上传图片</h4>
                            <img src="https://cdn.nlark.com/yuque/0/2024/png/21449790/1734155092010-6bbdfaa9-106f-4cdd-878e-ea6d267e46b5.png" alt="上传图片" class="rounded-lg shadow-sm w-full">
                        </div>
                        <div>
                            <h4 class="font-medium text-gray-700 mb-2">3. 识别结果</h4>
                            <img src="https://cdn.nlark.com/yuque/0/2024/png/21449790/1734155866450-8157228c-6fd7-45b4-9311-c19b4edaec71.png" alt="识别结果" class="rounded-lg shadow-sm w-full">
                        </div>
                    </div>
                </div>
            </div>
        </section>

        <!-- Summary Section -->
        <section class="bg-indigo-50 rounded-xl p-8 mb-12">
            <div class="max-w-3xl mx-auto text-center">
                <h2 class="text-2xl font-bold text-indigo-800 mb-4">掌握预训练模型的核心要点</h2>
                <div class="grid md:grid-cols-3 gap-6 mt-6">
                    <div class="bg-white p-4 rounded-lg shadow-sm">
                        <i class="fas fa-database text-indigo-600 text-2xl mb-3"></i>
                        <h3 class="font-semibold text-gray-800 mb-2">数据驱动</h3>
                        <p class="text-gray-600 text-sm">预训练模型依赖于大规模高质量数据集</p>
                    </div>
                    <div class="bg-white p-4 rounded-lg shadow-sm">
                        <i class="fas fa-exchange-alt text-indigo-600 text-2xl mb-3"></i>
                        <h3 class="font-semibold text-gray-800 mb-2">迁移学习</h3>
                        <p class="text-gray-600 text-sm">将通用知识迁移到特定任务中</p>
                    </div>
                    <div class="bg-white p-4 rounded-lg shadow-sm">
                        <i class="fas fa-tools text-indigo-600 text-2xl mb-3"></i>
                        <h3 class="font-semibold text-gray-800 mb-2">高效开发</h3>
                        <p class="text-gray-600 text-sm">减少训练时间，加速模型部署</p>
                    </div>
                </div>
            </div>
        </section>
    </div>

    <!-- Footer -->
    <footer class="bg-gray-900 text-gray-300 py-12">
        <div class="max-w-6xl mx-auto px-4 sm:px-6 lg:px-8">
            <div class="flex flex-col items-center">
                <div class="text-xl font-medium text-white mb-4">技术小馆</div>
                <a href="http://www.yuque.com/jtostring" class="text-indigo-400 hover:text-indigo-300 transition duration-300">
                    <i class="fas fa-external-link-alt mr-1"></i> http://www.yuque.com/jtostring
                </a>
                <div class="mt-6 flex space-x-6">
                    <a href="#" class="text-gray-400 hover:text-white transition duration-300">
                        <i class="fab fa-github text-xl"></i>
                    </a>
                    <a href="#" class="text-gray-400 hover:text-white transition duration-300">
                        <i class="fab fa-twitter text-xl"></i>
                    </a>
                    <a href="#" class="text-gray-400 hover:text-white transition duration-300">
                        <i class="fab fa-youtube text-xl"></i>
                    </a>
                </div>
            </div>
        </div>
    </footer>

    <script>
        mermaid.initialize({
            startOnLoad: true,
            theme: 'default',
            flowchart: {
                useMaxWidth: true,
                htmlLabels: true,
                curve: 'basis'
            }
        });
    </script>
</body>
</html>
```